tailieunhanh - Assessing Product Reliability_11

Tham khảo tài liệu 'assessing product reliability_11', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Lognormal or Weibull tests ENGINEERING STATISTICS HANDBOOK hW tools raids lỉEÂtCH BACK Nixf 8. Assessing Product Reliability . Reliability Data Collection . How do you plan a reliability assessment test . Lognormal or Weibull tests Planning reliability tests for distributions other than the exponential is difficult and involves a lot of guesswork Planning a reliability test is not simple and straightforward when the assumed model is lognormal or Weibull. Since these models have two parameters no estimates are possible without at least two test failures and good estimates require considerably more than that. Because of censoring without a good guess ahead of time at what the unknown parameters are any test plan may fail. However it is often possible to make a good guess ahead of time about at least one of the unknown parameters - typically the shape parameter f7 for the lognormal or for the Weibull . With one parameter assumed known test plans can be derived that assure the reliability or failure rate of the product tested will be acceptable. Lognormal Case shape parameter known The lognormal model is used for many microelectronic wear-out failure mechanisms such as electromigration. As a production monitor samples of microelectronic chips taken randomly from production lots might be tested at levels of voltage and temperature that are high enough to significantly accelerate the occurrence of electromigration failures. Acceleration factors are known from previous testing and range from several hundred to several thousand. http div898 handbook apr section3 1 of 4 5 1 2006 10 42 17 AM . Lognormal or Weibull tests Lognormal test plans assuming sigma and the acceleration factor are known The goal is to construct a test plan put n units on stress test for T hours and accept the lot if no more than r failures occur . The following assumptions are made A The life distribution model is lognormal Sigma rT is known .